1. Field of the Invention
This invention relates to processing a scanned image of a document (for example a paper document) to generate a document summary from the scanned image.
2. Description of Related Art
There are many occasions in which it would be desirable to compile automatically a summary of a document. Several approaches for such systems have been proposed in the prior art.
For example, European Patent Application EP 0902379 A2 describes a technique in which a user is able to mark certain words or phrases in an electronic version of a document (for example ASCII text), which the system then extracts to compile a document summary. However, such a system requires the user to work with an electronic version of the document. Furthermore, the document must already exist in the electronic form before any words or phrases can be selected by the user.
Regarding the summarizing of paper documents (or scanned images of paper documents), reference may be made to the following documents:
U.S. Pat. Nos. 5,638,543 and 5,689,716 describe systems in which paper document images are scanned and the images are processed using optical character recognition (OCR) to produce a machine-readable version of the document. A summary is generated by allocating “scores” to sentences depending on critical or thematic words detected in the sentence. The summary is generated from the sentences having the best scores.
U.S. Pat. No. 5,848,191 describes a system similar to U.S. Pat. No. 5,689,716 using scores to rank sentences, the score being dependent on the number of thematic words occurring in a sentence. However, in U.S. Pat. No. 5,848,191, the summary is generated directly from the scanned image without performing OCR.
U.S. Pat. No. 5,491,760 describes a system in which significant words, phrases and graphics in a document image are recognized using automatic or interactive morphological image recognition techniques. A document summary or an index can be produced based on the identified significant portions of the document image.
“Summarization Of Imaged Documents Without OCR” by Chen and Bloomberg, in Computer Vision and Image Understanding, Vol. 70, No. 3, June 1998, on pages 307-320, describes an elaborate technique based on feature extraction and scoring sentences based on the values of a set of discrete features. Prior information is used in the form of feature vector values obtained from summaries compiled by professional human summary compilers. The sentences to be included in the summary are chosen according to the score of the sentence.
The above paper based techniques all employ variations of statistical scoring to decide (either on the basis of OCR text or on the basis of image maps) which features, or sentences, should be extracted for use in the complied summary.